Abstract
Natural Language Processing (NLP) plays a pivotal role in the realm of Digital Humanities (DH) and serves as the cornerstone for advancing the structural analysis of historical and cultural heritage texts. This is particularly true for the domains of named entity recognition (NER) and relation extraction (RE). In our commitment to expediting ancient history and culture, we present the ``Chinese Historical Information Extraction Corpus''(CHisIEC). CHisIEC is a meticulously curated dataset designed to develop and evaluate NER and RE tasks, offering a resource to facilitate research in the field. Spanning a remarkable historical timeline encompassing data from 13 dynasties spanning over 1830 years, CHisIEC epitomizes the extensive temporal range and text heterogeneity inherent in Chinese historical documents. The dataset encompasses four distinct entity types and twelve relation types, resulting in a meticulously labeled dataset comprising 14,194 entities and 8,609 relations. To establish the robustness and versatility of our dataset, we have undertaken comprehensive experimentation involving models of various sizes and paradigms. Additionally, we have evaluated the capabilities of Large Language Models (LLMs) in the context of tasks related to ancient Chinese history. The dataset and code are available at \url{this https URL}.
Abstract (translated)
自然语言处理（NLP）在数字人文领域中扮演着关键角色，并作为研究历史和文化遗产文本结构分析的基础。这尤其是在命名实体识别（NER）和关系提取（RE）领域。在我们致力于加速古代历史和文化的承诺下，我们推出了“中文历史信息抽取数据集”（CHisIEC）。CHisIEC是一个精心挑选的数据集，旨在开发和评估NER和RE任务，为该领域的研究提供资源。该数据集涵盖了从13个王朝跨越超过1830年的历史数据的惊人历史时间轴，恰当地代表了中文历史文献中存在的广泛时间和文本异质性。数据集包括四个不同的实体类型和十二种关系类型，形成了一个包含14,194个实体和8,609个关系的 meticulously labeled 数据集。为了验证我们数据集的稳健性和多样性，我们进行了涉及各种大小和范式的全面实验。此外，我们还评估了大型语言模型（LLMs）在古代中国历史相关任务中的能力。数据集及其代码可在此处访问：https://this URL。
URL
https://arxiv.org/abs/2403.15088
